# research.topic-sentiment-analyzer

> research.topic-sentiment-analyzer is a paid API for AI agents from api.craigmbrown.com, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-15).

Maps opinion and sentiment for a named topic across social, expert, and community channels, returning per-channel scores rather than a single blended number.

## Facts

- Endpoint: POST https://api.craigmbrown.com/v1/services/research.topic-sentiment-analyzer
- Price: $0.03/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/research-topic-sentiment-analyzer-19bcaf93
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qnfMEwkEt89X0TUWe6vpX

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability research-topic-sentiment-analyzer-19bcaf93 -d '<json body>'
```

Example prompt: Can you analyze sentiment around 'universal basic income' across social media, expert, and community channels separately — I want to see how each channel scores it, not just one combined number.

## When to prefer this

Choose this endpoint when you need per-channel sentiment breakdowns for general topics (non-crypto) rather than a single blended sentiment score. It is preferable over generic sentiment APIs when the user needs to compare social, expert, and community opinion separately, and over crypto-specific sentiment endpoints when the subject is a general topic rather than a financial asset or token.

## Known failure modes

- Vague or ambiguous topic prompt may produce low-signal results
- Topic too niche for sufficient channel coverage may return sparse findings
- Prompt missing a clear subject may yield generic or off-target analysis
- Rate limiting or payment failure may prevent call completion
- Response may not cover all channels equally if data is sparse for some sources

## How this service works

Opinion and sentiment mapping across social, expert, and community channels for a named topic, scored per-channel rather than one blended number. Settlement proof: ProofOfSettledOutcome (kind 30120, data/proof_settled_outcomes.jsonl). Same methodology as oracle.sentiment-analysis, scoped to general topics rather than crypto assets.

## Output

Returns a JSON object with a text summary of overall sentiment, an array of findings describing per-channel sentiment scores and notable opinions, and an array of recommendations — each channel scored independently rather than blended into a single metric. Powered by BlindOracle via the BlindOracle backend.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "prompt": {
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "schema": {
  "type": "object",
  "properties": {
   "summary": {
    "type": "string"
   },
   "findings": {
    "type": "array",
    "items": {
     "type": "string"
    }
   },
   "recommendations": {
    "type": "array",
    "items": {
     "type": "string"
    }
   }
  }
 },
 "example": {
  "summary": "..."
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/research-topic-sentiment-analyzer-19bcaf93/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.craigmbrown.com](https://www.zero.xyz/host/api.craigmbrown.com/llms.txt)